As artificial intelligence (AI) technologies continue to expand rapidly across industries and society, concerns about their environmental footprint are intensifying. While the potential benefits of AI for economic growth, innovation, and climate solutions are significant, there remain crucial gaps in how AI’s environmental impact — including energy consumption, water use, greenhouse gas emissions, and electronic waste — is measured and managed. The pioneering ITU report “Measuring what matters: How to assess AI’s environmental impact” identified critical challenges such as reliance on indirect estimates, fragmented data across AI lifecycle stages, and a lack of standardized, transparent frameworks for reporting and accountability.
Capacity building, investment and collaboration: Turning AI standards into practice
Governments around the world are increasingly aligning around a shared set of aspirations for artificial intelligence: it should be safe,...
AI for Good | Global Summit
For AI to do good, people must remain in control
Trusted information, enforced boundaries and accountable decisions are the foundations of dependable AI, argued Philip Miller in an AI for...
AI for Good | Global Summit
Connecting the dots to trustworthy AI: IEC at AI for...
The burning questions around AI are no longer just about what technology can do. They are about how we can...
AI for Good | Global Summit
